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Understanding Research Methods in Psychology

Explore general principles of psychological research, from operational definitions to experimental designs. Learn about population samples, correlations, experiments, and more. Understand how to measure emotions and behaviors, and the importance of unbiased data collection.

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Understanding Research Methods in Psychology

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  1. A look at psychological research

  2. General principles • The specious attraction of anecdotes • The concern for precise measurement • Operational definitions – definitions which specify the procedure used to measure something • Also, a way to give a study’s focus of concern a numerical value • How do you measure anger, love, intelligence?

  3. Population samples • Population – the entire group of individuals of interest Sample – a small group chosen from the popu- lation

  4. Types of samples • Convenience – a sample chosen because of its availability • Far from ideal, but very common “The study of 20 year old college sophomores.” ? • Representative – a sample which closely mirrors the population in all characteristics likely to affect the results • Ideal but hard to find

  5. Samples cont. • Random samples – a sample in which every individual in the population has an equal chance of being selected. • Hard to get, but many benefits • Cross-cultural samples – samples which include groups from at least two separate cultures • Discuss concerns in Interpretations

  6. Research designs • Naturalistic observations • A careful examination of an individual’s or animal’s behavior in more or less natural conditions No manipulation, just observation Often the first step in generating hypothesis’

  7. Case histories • A thorough description of a person or small group of people with unusual or noteworthy qualities Another source of hypothesis’ Just a super-sized anecdote?

  8. surveys • A study of the prevalence of certain beliefs, behaviors, or attitudes based upon people’s responses to specific questions • Many problems: sampling nonchalance the questions bias

  9. correlations • A measure of the relationship between two variables • Variable – a measurable item that can vary in magnitude • Correlational study – a procedure in which the investigator measures the relationship between two variables without controlling either one

  10. Correlationsexamples • Between class attendance and final grade • Between hours worked and $ earned • Between smiles given and smiles received • Between miles run/week and 5k time • Between hours on internet and final grade • Between exercise sessions and weight • Between hair color and grade point average

  11. Correlations graphicexamples

  12. The correlation coefficient • R = the mathematical relationship between two variables, ranging from -1 to 1 • Positive correlations approach 1 • Negative correlations approach -1 • A R of 0 means that there is no relationship between the two variables • Look to R’s absolute value when assessing its strength

  13. Illusory correlations • An apparent relationship based upon casual observations of unrelated or weakly related events • Do people really get wild under a full moon? Does the weather affect arthritis symptoms?

  14. Correlations and causation • No matter how it might seem, correlations do not tell us about cause and effect • We never really know if changes in one variable affects the other, or • If a third, lurking, variable controls them both. • Correlations help us predict but not explain or control behavior or experience.

  15. experiments

  16. experiments • A study in which the investigator manipulates at least one variable while measuring at least one other variable • By adjusting one variable or factor, while keeping all other factors constant, we can determine if that factor causes changes in the other(s)

  17. More definitions:variables • Independent variable – the variable which is manipulated, or adjusted, by the investigator • Dependent variable – the variable which is measured by the investigator to determine the effects of the independent variable • Thoughtfully quantified through the operational definition

  18. Even more:groups • Experimental group – receives the treatment (independent variable) that the experiment was designed to test • Control group – handled exactly the same as the experimental group except for the independent variable • Control groups usually receive a placebo

  19. Hazards to be prepared for • Biased groups • to make sure that the experimental and control groups are as similar as possible, before being introduced to the independent variable we use random assignment • every participantmust have anequal chance of being placed in either the experimental or the control group

  20. more hazards • Even unconsciously, investigators want to see their hypothesis confirmed and unintentionally might distort the results • Also, the experiment’s participants might try to help prove the hypothesis Solution – Double blind – a procedure in which both the observer and the participant are unaware of which participants received which treatment and the experiment’s goals

  21. review • Hypothesis • Select Method & Operational Definition • Acquire Sample • Random Assignment of groups • Run experiment (double blind) • Collect and analyze results (data)

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